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Research Overview

Research Labs

  • Algorithms and Computational Biology Lab
    The Algorithms and Computational Biology Lab is interested in all aspects of the design and analysis of combinatorial algorithms. Ongoing research includes approximation algorithms, on-line algorithms, computational geometry, graph drawing, information retrieval, average-case analysis of algorithms, and computational complexity. We are especially interested in algorithmic problems arising from computational molecular biology, such as (multiple) sequence alignment, reconstruction of evolutionary trees, physical mapping, DNA microarray analysis, and genome-level gene dynamics.
  • Computer Architecture and Embedded System group (CARES)
    The Computer Architecture and Embedded System group (CARES) at UC Riverside has faculty members from both the Computer Science and Engineering Department and the Electrical and Computer Engineering Department. We conduct active research in the areas of system architecture, microarchitecture, embedded systems, compilers, reconfigurable computing, and CAD for VLSI integrated circuits. The CARES group receives substantial external funds and produces quality publications in top conferences and journals every year.
  • Center for Research and Education in Cyber Security and Privacy (CRESP)
    The center aims at designing novel approaches to building secure systems and enabling them to detect and tolerate attacks. We also seek to prepare talented engineers and researchers with the technical and problem solving skills in this area of national need.
  • Database Lab
    The Database Lab has several ongoing projects in the area of databases, including evolving databases, temporal databases, and spatiotemporal databases.
  • Multi-Aspect Data Lab (MAD Lab)
    The Multi-Aspect Data Lab is focusing on developing models and algorithms for modeling, analyzing, and extracting knowledge from large and highly-complex multi-aspect (or multimodal) data. In addition to efficient, flexible, and interpretable methods, the Lab is focusing on a variety of real-world applications, including social network analysis, graph mining, and fake news detection.
  • Networks and Communications Lab
    The Networks and Communications Lab works on a large spectrum of issues spanning Internet technology, mobile computing, and sensor networks. Topics investigated include: secure and robust routing, Internet measurements, BGP routing analysis and modeling, P2P network measurements, and intrusion detection.
  • Riverside Graphics Lab (RGL)
    The Riverside Graphics Lab facilitates leading-edge research in the areas of graphics, animation, and media. Current topics focus on physically based modeling and human animation based on motion examples.
  • Riverside Lab for Artificial Intelligence Research
    Our research interests range from dynamic systems to machine learning to machine vision. If it involves adaptation, we're interested.
  • RIverside Programming Languages and software Engineering lab (RIPLE)
    The RIPLE group conducts research in a broad range of topics in the areas of programming languages and software engineering: compilation and optimization for multi-core CPUs, fault localization using dynamic analysis, logic and stochastic verification, dynamic software updating, and understanding software evolution.
  • SPRUCe: SmartPhone Research at UCr
    The SPRUCe group conducts research in virtually all aspects of smartphone analysis, from energy consumption and network traffic, to app analysis (static, dynamic), to testing and verification, to user and empirical studies, to protecting privacy on social networks and optimizing the interaction between apps and the cloud.
  • SuperLab
    The Supercomputing Laboratory (SuperLab) at the University of California, Riverside conducts research and development in the broad area of high performance computing. The mission of the laboratory is to develop techniques, design algorithms, and build software tools for computational science applications to achieve both high performance and high energy efficiency on a wide range of computational platforms.

 
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